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Prof. Dr. Jonghyuk Kim
SUNMOON University

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0 Behavior Analysis
0 Retail Analysis
0 Computer Science and Engineering
0 Sensor Applications
0 Manufacturing sustainable development system

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Journal article
Published: 14 April 2021 in Applied Sciences
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This study explores changes in a set of brand considerations as a result of web search strategies. Survey and personal computer log data of car buyers were used to identify online information search behavior for brands and products. Through this study, we found that higher frequencies of brand searching are associated with how much consumer-initiated sites and third-party-initiated sites are used, while lower frequencies of brand searching are only related to how much brand-initiated websites are used. We also concluded that ambivalent messages on consumer-initiated sites lead to the postponement of a decision and a continued search for another brand. In addition, third party-initiated information sources lower search costs, which lead to longer consumer journeys and expand the set of brands considered and searched. The results of this study can help marketers understand the importance of their own media and aid in the development of a digital media strategy.

ACS Style

Sungeun Kwon; Jonghyuk Kim; Zoonky Lee. Advances in Search Strategy Using the Set of Brand Considerations in the Web Ecosystem. Applied Sciences 2021, 11, 3514 .

AMA Style

Sungeun Kwon, Jonghyuk Kim, Zoonky Lee. Advances in Search Strategy Using the Set of Brand Considerations in the Web Ecosystem. Applied Sciences. 2021; 11 (8):3514.

Chicago/Turabian Style

Sungeun Kwon; Jonghyuk Kim; Zoonky Lee. 2021. "Advances in Search Strategy Using the Set of Brand Considerations in the Web Ecosystem." Applied Sciences 11, no. 8: 3514.

Journal article
Published: 17 March 2021 in Applied Sciences
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This study indirectly verifies the possibility of telemedicine for humans through a mobile application (app) targeting pets. It examined the perception of telemedicine services and the current status of the companion animal industry, the app platform, and its applied technology by industry domain, and four representative types of artificial intelligence (AI) technologies applicable in the medical field. A survey was conducted through an app implementing pet telemedicine, and hypotheses were established and statistically tested based on the adoption period of pets, health status, mobile service utilization (as an index measuring the ease of use of recent AI functions), and positive and negative perceptions of telemedicine services. As revealed by prospect theory, users with a negative perception of pet telemedicine tended to maintain negative perceptions about telemedicine for humans. This study proved that the severity of pet diseases and the ease of use of recent AI technologies act as a moderating effect on the perception of telemedicine services through the verification of reinforcement and additional hypotheses. It suggests a plan to overcome sanctions against telemedicine by utilizing AI technology. A positive effect on changing the medical paradigm to telemedicine and the improvement of the medical legal system were also observed.

ACS Style

Sewoong Hwang; YunGyeong Song; Jonghyuk Kim. Evaluation of AI-Assisted Telemedicine Service Using a Mobile Pet Application. Applied Sciences 2021, 11, 2707 .

AMA Style

Sewoong Hwang, YunGyeong Song, Jonghyuk Kim. Evaluation of AI-Assisted Telemedicine Service Using a Mobile Pet Application. Applied Sciences. 2021; 11 (6):2707.

Chicago/Turabian Style

Sewoong Hwang; YunGyeong Song; Jonghyuk Kim. 2021. "Evaluation of AI-Assisted Telemedicine Service Using a Mobile Pet Application." Applied Sciences 11, no. 6: 2707.

Journal article
Published: 13 March 2021 in Sustainability
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This study examines technology effectiveness for industry demand in which artificial intelligence (AI) is applied in the financial sector. It summarizes prior studies on chatbot and customer service and investigates theories on acceptance attitudes for innovative technologies. By setting variables, the study examines bank revenue methodologically and assesses the impact of customer service and chatbot on bank revenues through customer age classification. The results indicate that new product-oriented funds or housing subscription savings are more suitable for purchase through customer service than through chatbot. However, services for existing products through chatbot positively affect banks’ net income. When classified by age, purchases by the majority age group in the channel positively affect bank profits. Finally, there is a tendency to process small banking transactions through the chatbot system, which saves transaction and management costs, positively affecting profits. Through empirical analysis, we first examine the effect of an AI-based chatbot system implemented to strengthen financial soundness and suggest policy alternatives. Second, we use banking data to increase the study’s real-life applicability and prove that problems in customer service can be solved through a chatbot system. Finally, we investigate how resistance to technology can be reduced and efficiently accommodated.

ACS Style

Sewoong Hwang; Jonghyuk Kim. Toward a Chatbot for Financial Sustainability. Sustainability 2021, 13, 3173 .

AMA Style

Sewoong Hwang, Jonghyuk Kim. Toward a Chatbot for Financial Sustainability. Sustainability. 2021; 13 (6):3173.

Chicago/Turabian Style

Sewoong Hwang; Jonghyuk Kim. 2021. "Toward a Chatbot for Financial Sustainability." Sustainability 13, no. 6: 3173.

Journal article
Published: 13 November 2020 in Electronics
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Seoul Metropolitan City’s buses cater to more than 50% of the average daily public transportation use, and they are the most important transportation mode in Korea, together with the subway. Since 2004, all public transportation records of passengers have been stored in Seoul, using smart transportation cards. This study explores the environmental and psychological factors in implementing a smart transportation system. We analyze the switching behavior of traffic users according to traffic congestion time and number of transfers based on public transportation data and show that bus-use behavior differs according to the traffic information of users and the degree of traffic congestion. Information-based switching behavior of people living near bus stops induces people to change routes during traffic congestion. However, in non-congested situations, the original routes are used. These results can guide the formulation of policy measures on bus routes. We made it possible to continuously change the routes for certain buses, which were temporarily implemented due to traffic congestion. Moreover, we added a service that posts the estimated arrival time to major stops while reflecting real-time traffic conditions in addition to the bus location and arrival time information through the global positioning system.

ACS Style

Zoonky Lee; Sewoong Hwang; Jonghyuk Kim. Optimal Planning of Real-Time Bus Information System for User-Switching Behavior. Electronics 2020, 9, 1903 .

AMA Style

Zoonky Lee, Sewoong Hwang, Jonghyuk Kim. Optimal Planning of Real-Time Bus Information System for User-Switching Behavior. Electronics. 2020; 9 (11):1903.

Chicago/Turabian Style

Zoonky Lee; Sewoong Hwang; Jonghyuk Kim. 2020. "Optimal Planning of Real-Time Bus Information System for User-Switching Behavior." Electronics 9, no. 11: 1903.

Journal article
Published: 20 November 2019 in Sustainability
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The application of smart city technologies requires new data analysis methods to interpret the voluminous data collected. In this study, we first analyzed the transfer behavior of subway pedestrians using the fingerprinting technique using data collected by more than 100 MAC (Media Access Control) ID sensors installed in a congested subway station serving two subway lines. We then developed a model that employs an AI (Artificial Intelligence)-based methodology, the cumulative visibility of moving objects (CVMO), to present the data in such a manner that it could be used to address pedestrian flow issues in this real-world implementation of smart city technology. The MAC ID location data collected during a three-month monitoring period were mapped using the fingerprinting wireless location sensing method to display the congestion situation in real time. Furthermore we developed a model that can inform immediate response to identified conditions. In addition, we formulated several schemes for disbursing congestion and improving pedestrian flow using behavioral economics, and then confirmed their effectiveness in a follow-up monitoring period. The proposed pedestrian flow analysis method cannot only solve pedestrian congestion, but can also help to prevent accidents and maintain public order.

ACS Style

Sewoong Hwang; Zoonky Lee; Jonghyuk Kim. Real-Time Pedestrian Flow Analysis Using Networked Sensors for a Smart Subway System. Sustainability 2019, 11, 6560 .

AMA Style

Sewoong Hwang, Zoonky Lee, Jonghyuk Kim. Real-Time Pedestrian Flow Analysis Using Networked Sensors for a Smart Subway System. Sustainability. 2019; 11 (23):6560.

Chicago/Turabian Style

Sewoong Hwang; Zoonky Lee; Jonghyuk Kim. 2019. "Real-Time Pedestrian Flow Analysis Using Networked Sensors for a Smart Subway System." Sustainability 11, no. 23: 6560.

Journal article
Published: 06 November 2019 in Sustainability
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Retailers need accurate movement pattern analysis of human-tracking data to maximize the space performance of their stores and to improve the sustainability of their business. However, researchers struggle to precisely measure customers’ movement patterns and their relationships with sales. In this research, we adopt indoor positioning technology, including wireless sensor devices and fingerprinting techniques, to track customers’ movement patterns in a fashion retail store over four months. Specifically, we conducted three field experiments in three different timeframes. In each experiment, we rearranged one element of the visual merchandising display (VMD) to track and compare customer movement patterns before and after the rearrangement. For the analysis, we connected customers’ discrete location data to identify meaningful patterns in customers’ movements. We also used customers’ location and time information to match identified movement pattern data with sales data. After classifying individuals’ movements by time and sequences, we found that stay time in a particular zone had a greater impact on sales than the total stay time in the store. These results challenge previous findings in the literature that suggest that the longer customers stayed in a store, the more they purchase. Further, the results confirmed that effective store rearrangement could change not only customer movement patterns but also overall sales of store zones. This research can be a foundation for various practical applications of tracking data technologies.

ACS Style

Jonghyuk Kim; Hyunwoo Hwangbo; Sung Jun Kim; SoYean Kim. Location-Based Tracking Data and Customer Movement Pattern Analysis Using for Sustainable Fashion Business. Sustainability 2019, 11, 6209 .

AMA Style

Jonghyuk Kim, Hyunwoo Hwangbo, Sung Jun Kim, SoYean Kim. Location-Based Tracking Data and Customer Movement Pattern Analysis Using for Sustainable Fashion Business. Sustainability. 2019; 11 (22):6209.

Chicago/Turabian Style

Jonghyuk Kim; Hyunwoo Hwangbo; Sung Jun Kim; SoYean Kim. 2019. "Location-Based Tracking Data and Customer Movement Pattern Analysis Using for Sustainable Fashion Business." Sustainability 11, no. 22: 6209.

Journal article
Published: 09 June 2019 in Sustainability
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Many previous studies have shown that the volume or valence of electronic word of mouth (eWOM) has a sustainable and significant impact on box office performance. Traditional studies used quantitative data, such as ratings, to measure eWOM. However, recent studies analyzed unstructured data, such as comments, through web-based text analysis. Based on recent research trends, we analyzed not only quantitative data, like ratings, but also text data, like reviews, and we performed a sentiment analysis using a text mining technique. Studies have also examined the effect of cultural differences on the decision-making processes of individuals and organizations. We applied Hofstede’s cultural theory to eWOM and analyzed the moderating effect of cultural differences on eWOM influence. We selected 338 films released between 2006 and 2015 from the BoxOfficeMojo database. We collected ratings and reviews, box office revenues, and other basic information from the Internet Movie Database (IMDb). We also analyzed the effects of cultural differences, such as power distance, individualism, uncertainty avoidance, and masculinity, on box office performance. We found that user comments have a greater impact on film sales than user ratings, and movie stars and co-production contribute to box office success. We also conclude that cultural and geographical differences moderate the sentiment elasticity of eWOM.

ACS Style

Hyunwoo Hwangbo; Jonghyuk Kim. A Text Mining Approach for Sustainable Performance in the Film Industry. Sustainability 2019, 11, 3207 .

AMA Style

Hyunwoo Hwangbo, Jonghyuk Kim. A Text Mining Approach for Sustainable Performance in the Film Industry. Sustainability. 2019; 11 (11):3207.

Chicago/Turabian Style

Hyunwoo Hwangbo; Jonghyuk Kim. 2019. "A Text Mining Approach for Sustainable Performance in the Film Industry." Sustainability 11, no. 11: 3207.

Journal article
Published: 12 March 2019 in Sustainability
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In this study, real-time preventive measures were formulated for a crusher process that is impossible to automate, due to the impossibility of installing sensors during the production of plastic films, and a real-time early warning system for semi-automated processes subsequently developed. First, the flow of a typical film process was ascertained. Second, a sustainable plan for real-time forecasting in a process that cannot be automated was developed using the semi-automation method flexible structure production control (FSPC). Third, statistical early selection of the process variables that are most probably responsible for failure was performed during data preprocessing. Then, a new, unified dataset was created using the link reordering method to transform the time sequence of the continuous process into one time zone. Fourth, a sustainable prediction algorithm was developed using the association rule method along with traditional statistical techniques, and verified using actual data. Finally, the overall developed logic was applied to new production process data to verify its prediction accuracy. The developed real-time early warning system for semi-automated processes contributes significantly to the smart manufacturing process both theoretically and practically.

ACS Style

Jonghyuk Kim; Hyunwoo Hwangbo. Real-Time Early Warning System for Sustainable and Intelligent Plastic Film Manufacturing. Sustainability 2019, 11, 1490 .

AMA Style

Jonghyuk Kim, Hyunwoo Hwangbo. Real-Time Early Warning System for Sustainable and Intelligent Plastic Film Manufacturing. Sustainability. 2019; 11 (5):1490.

Chicago/Turabian Style

Jonghyuk Kim; Hyunwoo Hwangbo. 2019. "Real-Time Early Warning System for Sustainable and Intelligent Plastic Film Manufacturing." Sustainability 11, no. 5: 1490.